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ANOVA complex design

ANOVA complex design. What is in a results section??? LOOK at the example in your textbook. You need to have subheading. You need to have figures and they must have useful figure captions. You must refer to your figures. You need to describe the data in some way

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ANOVA complex design

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  1. ANOVA complex design

  2. What is in a results section??? LOOK at the example in your textbook. You need to have subheading. You need to have figures and they must have useful figure captions. You must refer to your figures. You need to describe the data in some way You need to describe the analyses and what you found. Is it significant? Or not Then add some English to describe what you found.

  3. e.g To examine the effects of memory training on retention of words, 20 college students were randomly assigned to four training conditions (n=5) defined by the instructions to participants: story method, imagery method, rhyme method, and control (no specific instructions). Mean recall out of a possible 20 words (and the sample standard deviation) for each condition was: story 13.2(1.3), imagery 14.4 (1.8), rhyme 13.4 (1.3) and control 10.0 (1.6). Confidence intervals for the means in each group are shown in figure 1. Mean recall differed significantly among the four instruction conditions, F(3,16) = 7.8, p<.05. MS = 240…. A paragraph that describes what is compared and what you found. Where I should look to find the information.

  4. Reporting results of complex design • What kind of test • description of variables and definitions of levels (conditions) of each • summary statistics for cells in design matrix (figure) • report F tests for main effects and interactions • effect size • statement of power for nonsignificant results • simple main effects analysis when interaction is statistically significant • description of statistically significant interactions – looking at cell means • description of statistically significant main effect • analytical comparisons – to clarify sources of systematic variation • conclusion from analysis

  5. Car Noise The data are from a statement by Texaco, Inc. to the Air and Water Pollution Subcommittee of the Senate Public Works Committee on June 26, 1973. Mr. John McKinley, President of Texaco, cited the Octel filter, developed by Associated Octel Company as effective in reducing pollution. However, questions had been raised about the effects of pollution filters on aspects of vehicle performance, including noise levels. He referred to data presented in the datafile associated with this story as evidence that the Octel filter was was at least as good as a standard silencer in controlling vehicle noise levels.

  6. The data constitute a 3-way factorial experiment with 3 replications. The factors are type of filter (2 types), vehicle size (3 sizes), and side of car (two sides).

  7. Number of cases = 36 DV NOISE = Noise level reading (decibels) IV SIZE = Vehicle size: 1 small, 2 medium, 3 large TYPE = 1 standard silencer ,2 Octel filter SIDE = 1 right side 2 left side of car

  8. Main effect Size is significant Mean small 824.16 sd = 7.63 Mean medium 833.75 sd =13.5 Mean large 772.50 sd= 10.33 Need post hoc tests Main effect Type is significant Standard mean 815.56 sd =32.2 Octel mean 804.72 sd =25.63 Don’t need post hoc tests

  9. All sizes differ.

  10. Interaction Size by Side is significant Need to find out where is the difference Simple main effects analysis Do t-test for the small And one for the medium And one for large One anova for left side One anova for right side

  11. side s m L

  12. Small size left bigger than right • Medium size no difference • Large size right bigger than left

  13. Right

  14. Left

  15. On right - small cars louder than large - medium cars louder than large - small cars quieter than medium • On left - small cars louder than large - medium cars louder than large

  16. Interaction Size by Type is significant Need to find out where is the difference Simple main effects analysis Do t-test for the small And one for the medium And one for large One for type standard One for type Octel

  17. s m L

  18. Standard

  19. Octel

  20. significant 3-way interaction. Size by type by side Need to separate the factors so can do 2-way analyses Hold one factor constant and test other Eg do a 2X2 of small cars 2X2 of medium and 2X2 of large….

  21. Small car – type by side

  22. Test small car Side is significant - left bigger than right Interaction is significant

  23. Small car Type : t –tests for the interaction Right Octel louder than standard Left

  24. Small car – t-tests for side Standard Left louder than right Octel

  25. Medium car - type by side

  26. Test Medium car Type is significant – standard louder than Octel

  27. Large car – type by side

  28. Test large car Side is significant – right is louder than left Interaction is significant -

  29. Large car Type : t –tests for the interaction Right Standard louder than octel Left

  30. Standard Octel

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